Service Parts Management: The Linchpin to Successful Service Operations
According to Gartner, the typical company provides support services and parts for an average of more than seven years after an initial product sale. Aftermarket parts and service have profit margins as much as 10 times those for initial product sales, and post-sale service is key to securing customer loyalty, fostering the company brand, and maintaining competitive differentiation.
All told, aftermarket service and parts
account for 20% to 30% of revenues and about 40% of total profits for most manufacturers.
Service Parts Planning and Optimization (SPP) is the linchpin of any effective service operation. SPP is the process of planning and aligning service parts inventories, resources, and processes to ensure optimal customer service and response with minimal risk and cost. According to Gartner research, the five most common goals for (SPP) are:
- Increase forecast accuracy for service parts
- Reduce excess spare parts inventory
- Reduce obsolete spare parts inventory
- Enhance scrapping programs
- Increase service levels by increasing fill rates, increasing product availability or up-time
Spare parts and services for previously purchased assets, such as automobiles, aircraft and industrial machinery, account for 8% of the annual gross domestic product in the United States. On a global basis, spending on such aftermarket parts and services totals more than $1.5 trillion annually.
There are multiple components to effective aftermarket service, including call centers, returns management operations, and promotions and marketing. However, the key driver of effective post-sale support is service parts management: the process of planning and aligning service parts inventories, resources, and processes to ensure optimal customer service and response with minimal risks and costs.
The biggest challenge is how to plan for products that have intermittent demand, also known as lumpy demand. The best approach to managing intermittent demand is a stochastic, adaptive method.